1. Field of the Invention
The present invention relates to an audio signal subband encoder used for low bit rate coding in recording/reproducing systems such as tapes and disks and transmission systems such as communication and broadcast.
2. Description of the Prior Art
In recent years, audio signal subband encoders have attracted public attention as apparatuses realizing low bit rate coding of high-quality audio signals.
Audio signal subband encoders of the prior art are described in a paper (hereafter referred to as paper 1) written by G. Theile et al., presented in EBU Review Technical, No. 230, pp. 71-94, August 1988, and entitled "Low bit-rate coding of high-quality audio signals, an introduction to MASCAM system" and a paper (hereafter referred to as paper 2) written by R. N. J. Veldhuis et al., presented in Philips Journal of Research, Vol. 44, No. 2/3, pp. 329-343, 1989, and entitled "Subband coding of digital audio signals", for example.
Audio signal subband encoders and their decoders of the prior art will hereafter be described by referring to drawings.
FIG. 1 shows a block diagram of an audio signal subband encoder of the prior art.
With reference to FIG. 1, numeral 11 denotes an analysis filter, 12 a peak information decision unit, 13 an evaluation function calculator, 14 a bit allocation decision unit, 15 a quantizer, and 16 a multiplexer.
Operation of the audio signal subband encoder configured as heretofore described will hereafter be described.
In FIG. 1, the analysis filter 11 is a filter bank including a plurality of band pass filters for dividing an inputted digital audio signal into a plurality of subbands. The analysis filter 11 includes an integer-band filter bank. Integer-band filter banks are described in Chapter 11 (hereafter referred to as paper 3) of a book written by N. S. Jayant and P. Noll, published in 1984 by Prentice-Hall, and entitled "Digital coding of waveforms". In the integer-band filter bank, the ratio of the entire bandwidth to the bandwidth of a subband is an integer and decimation is performed with this ratio to downsample and convert a band pass signal to a low pass signal. At band boundaries, however, aliasing distortion is caused by the decimation. As filters capable of cancelling this aliasing distortion by using synthesis filters, quadrature mirror filters (hereafter referred to as QMFs) are widely used. QMFs are filters capable of cancelling aliasing distortion when quantization step sizes of the signals in adjacent subbands are equal. In the analysis filter 11, the signal divided into a plurality of subbands are partitioned into frames having predetermined times.
The peak information decision unit 12 derives the peak of the absolute values of signals into frames for every subband supplied from the analysis filter 11 and outputs peak information.
On the basis of the human auditory masking rule, the evaluation function calculator 13 calculates an evaluation function required for performing appropriate bit allocation in the bit allocation decision unit 14. That is to say, letting the number of subbands be N, subband No. be i (where Nos. are assigned in order from a low frequency to a high frequency, 1.ltoreq.i.ltoreq.N), peak information of a subband No. i be P.sub.i, signal power of the subband No. i be S.sub.i, threshold of power of the subband No. i masked by the signal (hereafter referred to as masked power) be M.sub.i, the number of samples of the subband No. i signal in one frame be L.sub.i, the number of quantization bits of a sample be b.sub.i, and the number of all bits allocatable to sample information in one frame be B.sub.q, quantization noise power of subband No. i is derived by the following expression. EQU (2P.sub.i /2.sup.bi).sup.2 /12
Therefore, the ratio of quantization noise power of the entire band to masked power (hereafter referred to as noise-to-mask ratio) is given by the following expression. ##EQU1## The bit allocation decision unit 14 performs such bit allocation so as to minimize the noise-to-mask ratio under the condition expressed by the following equation. ##EQU2## In order to perform bit allocation in the stated way, the evaluation function calculator 13 makes a calculation of the following equation as an evaluation function E.sub.i of subband No. i. ##EQU3##
FIG. 2 is a flow chart of an evaluation function calculator 13 of the prior art. In the evaluation function calculator 13, signal power in each subband is first calculated by using the signal of each subband supplied from the analysis filter 11. On the basis of the signal power of each subband and the masking rule, masked power which is masked by the signal in the subband itself and the signal in adjacent subbands and hence which is not audible to human ears, is then calculated. The evaluation function is then derived and outputted by subtracting half of the logarithm of the masked power to the base 2 from the logarithm of the peak information supplied from the peak information decision unit 12 to the base 2.
FIG. 3 is a flow chart of the bit allocation decision unit 14 of the prior art. The bit allocation decision unit 14 performs initialization processing at step 1 and thereafter repeats steps 2 and 3. Thereby the bit allocation decision unit 14 decides on and outputs the number bi of bits allocated to the subband No. i which minimizes the noise-to-mask ratio.
At step 1, the number B of remaining allocatable bits is set at B.sub.q and bi (1.ltoreq.i.ltoreq.N) is set at 0.
At Step 2, the subband No. k which makes the evaluation function E.sub.i the maximum value E.sub.max is found.
At Step 3, L.sub.k is substrated from the number B of remaining allocatable bits. If B is greater than or equal to 0, then the number b.sub.k of bits allocated to this subband is increased by one, one is subtracted from the evaluation function E.sub.k, and thereafter the processing returns to the step 2. If B is negative, then the bit allocation processing is finished, and the number bi of bits at the time of finish is outputted as bit allocation information.
The quantizer 15 normalizes the signal of each frame of each subband supplied from the analysis filter 11 by using the peak information supplied from the peak information decision unit 12, quantizes the signal of each subband in accordance with bit allocation information supplied from the bit allocation decision unit 14, and outputs the result as sample information.
The multiplexer 16 multiplexes the sample information of each subband supplied from the quantizer 15, the peak information of each subband supplied from the peak information decision unit 12, and the bit allocation information of each subband supplied from the bit allocation decision unit 14. The multiplexer 16 thus outputs a coded signal.
FIG. 4 shows a block diagram of an audio signal subband decoder of the prior art for decoding signals encoded by the audio signal subband encoder.
With reference to FIG. 4, numeral 41 denotes a demultiplexer, 42 a dequantizer, and 43 a synthesis filter.
Operation of the audio signal subband decoder configured as heretofore described will hereafter be described.
In FIG. 4, the demultiplexer 41 separates the inputted coded signal into respective frames, separates the signal of each frame into sample information, peak information and bit allocation information, and outputs them. For each subband, the dequantizer 42 dequantizes the sample information supplied from the demultiplexer 41 by using the bit allocation information, then performs denormalization using the peak information, and reproduces the signal of each frame of each subband. The synthesis filter 43 upsamples the signal of each subband supplied from the dequantizer 42 up to the original sample frequency by inserting 0es into the signal and performing interpolation, and reproduces and outputs a digital audio signal by adding signals passed through a synthesis band pass filter bank paired with the analysis filter bank. Therefore, the aliasing distortion of the reproduced digital audio signal is superpositioned of characteristics of two subband filters, i.e., the analysis filter and the synthesis filter.
In the above described audio signal subband encoder of the prior art, however, an error was caused in masked power by an approximation error in applying the masking rule and bit allocation was performed on the basis of an evaluation function including the error. Therefore, the audio signal subband encoder had a problem of degraded quality of audio signals. That is to say, the effect of the aliasing distortion generated by subband filters at the time of application of the masking rule was not considered in the audio signal subband encoder of the prior art. Therefore, unmasked noises due to aliasing distortion were caused especially in low frequency subbands having small masking effects, resulting in degraded quality of sound in some cases. Further, there was also an error caused by applying the masking rule based upon a sine wave signal and a narrow band noise signal to an actual signal having complicated frequency spectra. Further, when the bit rate was increased in order to improve the transparency with respect to the original signal, bit allocation was not optimum due to the influence of the above described errors and hence a difference from the original signal remained, resulting in a problem.